coronavirus an investigation of transmission control ... · coronavirus an investigation of...

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CORONAVIRUS An investigation of transmission control measures during the first 50 days of the COVID-19 epidemic in China Huaiyu Tian 1 *, Yonghong Liu 1 * , Yidan Li 1 * , Chieh-Hsi Wu 2 * , Bin Chen 3 * , Moritz U. G. Kraemer 4,5,6 , Bingying Li 1 , Jun Cai 7 , Bo Xu 7 , Qiqi Yang 1 , Ben Wang 1 , Peng Yang 8 , Yujun Cui 9 , Yimeng Song 10 , Pai Zheng 11 , Quanyi Wang 8 , Ottar N. Bjornstad 12,13 , Ruifu Yang 9 , Bryan T. Grenfell 14,15 , Oliver G. Pybus 4 , Christopher Dye 4,16 Responding to an outbreak of a novel coronavirus [agent of coronavirus disease 2019 (COVID-19)] in December 2019, China banned travel to and from Wuhan city on 23 January 2020 and implemented a national emergency response. We investigated the spread and control of COVID-19 using a data set that included case reports, human movement, and public health interventions. The Wuhan shutdown was associated with the delayed arrival of COVID-19 in other cities by 2.91 days. Cities that implemented control measures preemptively reported fewer cases on average (13.0) in the first week of their outbreaks compared with cities that started control later (20.6). Suspending intracity public transport, closing entertainment venues, and banning public gatherings were associated with reductions in case incidence. The national emergency response appears to have delayed the growth and limited the size of the COVID-19 epidemic in China, averting hundreds of thousands of cases by 19 February (day 50). O n 31 December 2019less than a month before the 2020 Spring Festival holiday, including the Chinese Lunar New Yeara cluster of pneumonia cases caused by an unknown pathogen was reported in Wuhan, a city of 11 million inhabitants and the largest transport hub in Central China. A novel coronavirus (1, 2) was identified as the etiolog- ical agent (3, 4), and human-to-human trans- mission of the virus [severe acute respiratory syndromecoronavirus 2 (SARS-CoV-2)] has been since confirmed (5, 6). Further spatial spread of this disease was of great concern in view of the upcoming Spring Festival ( chunyun), during which there are typically 3 billion travel movements over the 40-day holiday period, which runs from 15 days before the Spring Festival (Chinese Lunar New Year) to 25 days afterward (7, 8). Because there is currently neither a vaccine nor a specific drug treatment for coronavirus disease 2019 (COVID-19), a range of public health (nonpharmaceutical) interventions has been used to control the epidemic. In an at- tempt to prevent further dispersal of COVID- 19 from its source, all transport was prohibited in and out of Wuhan city from 10:00 a.m. on 23 January 2020, followed by the whole of Hubei Province a day later. In terms of the population covered, this appears to be the largest attempted cordon sanitaire in human history. On 23 January, China also raised its national public health response to the highest state of emergency: Level 1 of 4 levels of severity in the Chinese Emergency System, defined as an extremely serious incident(9). As part of the national emergency response, and in addition to the Wuhan city travel ban, suspected and confirmed cases have been isolated, public transport by bus and subway rail suspended, schools and entertainment venues have been closed, public gatherings banned, health checks carried out on migrants (floating population), travel prohibited in and out of cities, and in- formation widely disseminated. Despite all of these measures, COVID-19 remains a danger in China. Control measures taken in China potentially hold lessons for other countries around the world. Although the spatial spread of infectious diseases has been intensively studied (1015), including explicit studies of the role of human movement (16, 17), the effectiveness of travel restrictions and social distancing measures in preventing the spread of infection is uncertain. For COVID-19, SARS-CoV-2 transmission pat- terns and the impact of interventions are still poorly understood (6, 7). We therefore carried out a quantitative analysis to investigate the role of travel restrictions and transmission con- trol measures during the first 50 days of the COVID-19 epidemic in China, from 31 December 2019 to 19 February 2020 (Fig. 1). This period encompassed the 40 days of the Spring Festival holiday, 15 days before the Chinese Lunar New Year on 25 January and 25 days afterward. The analysis is based on a geocoded repository of data on COVID-19 epidemiology, human move- ment, and public health (nonpharmaceutical) interventions. These data include the numbers of COVID-19 cases reported each day in each city of China, information on 4.3 million human movements from Wuhan city, and data on the timing and type of transmission control mea- sures implemented across cities of China. We first investigated the role of the Wuhan city travel ban, comparing travel in 2020 with that in previous years and exploring how holi- day travel links to the dispersal of infection across China. During Spring Festival travel in 2017 and 2018, there was an average outflow of 5.2 million people from Wuhan city during the 15 days before the Chinese Lunar New Year. RESEARCH Tian et al., Science 368, 638642 (2020) 8 May 2020 1 of 5 1 State Key Laboratory of Remote Sensing Science, College of Global Change and Earth System Science, Beijing Normal University, Beijing, China. 2 School of Mathematical Sciences, University of Southampton, Southampton, UK. 3 Department of Land, Air and Water Resources, University of California Davis, Davis, CA, USA. 4 Department of Zoology, University of Oxford, Oxford, UK. 5 Harvard Medical School, Harvard University, Boston, MA, USA. 6 Boston Childrens Hospital, Boston, MA, USA. 7 Ministry of Education Key Laboratory for Earth System Modeling, Department of Earth System Science, Tsinghua University, Beijing, China. 8 Beijing Center for Disease Prevention and Control, Beijing, China. 9 State Key Laboratory of Pathogen and Biosecurity, Beijing Institute of Microbiology and Epidemiology, Beijing, China. 10 Department of Urban Planning and Design, The University of Hong Kong, Hong Kong. 11 Department of Occupational and Environmental Health Sciences, School of Public Health, Peking University, China. 12 Center for Infectious Disease Dynamics, Department of Biology, Pennsylvania State University, University Park, PA, USA. 13 Department of Entomology, College of Agricultural Sciences, Pennsylvania State University, University Park, PA, USA. 14 Division of International Epidemiology and Population Studies, Fogarty International Center, National Institutes of Health, Bethesda, MD, USA. 15 Department of Ecology and Evolutionary Biology, Princeton University, Princeton, NJ, USA. 16 Oxford Martin School, University of Oxford, Oxford, UK. *These authors contributed equally to this work. Corresponding author. Email: [email protected] (H.T.); [email protected] (C.D.); [email protected] (O.G.P.); [email protected] (B.T.G.); [email protected] (R.Y.) Table 1. Associationbetween the Wuhan travel ban and COVID-19 dispersal to other cities in China. The dependent variable Y is the arrival time (days) of the outbreak in each city. Covariates Coefficient 95% CI P Intercept 25.95 (23.43, 28.48) <0.01 ..................................................................................................................................................................................................................... Longitude (degrees) 0.03 (0.05, 0.01) <0.01 ..................................................................................................................................................................................................................... Latitude (degrees) 0.03 (0.01, 0.06) <0.05 ..................................................................................................................................................................................................................... log10 (population) 0.70 (1.12, 0.28) <0.01 ..................................................................................................................................................................................................................... log10 (total movements) 0.12 (0.22, 0.02) <0.05 ..................................................................................................................................................................................................................... Travel ban (days) 2.91 (2.54, 3.29) <0.01 ..................................................................................................................................................................................................................... Corrected 8 May 2020. See full text. on November 21, 2020 http://science.sciencemag.org/ Downloaded from

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Page 1: CORONAVIRUS An investigation of transmission control ... · CORONAVIRUS An investigation of transmission control measures during the first 50 days of the COVID-19 epidemic in China

CORONAVIRUS

An investigation of transmission control measuresduring the first 50 days of the COVID-19 epidemicin ChinaHuaiyu Tian1*†, Yonghong Liu1*, Yidan Li1*, Chieh-Hsi Wu2*, Bin Chen3*, Moritz U. G. Kraemer4,5,6,Bingying Li1, Jun Cai7, Bo Xu7, Qiqi Yang1, Ben Wang1, Peng Yang8, Yujun Cui9, Yimeng Song10,Pai Zheng11, Quanyi Wang8, Ottar N. Bjornstad12,13, Ruifu Yang9†, Bryan T. Grenfell14,15†,Oliver G. Pybus4†, Christopher Dye4,16†

Responding to an outbreak of a novel coronavirus [agent of coronavirus disease 2019 (COVID-19)]in December 2019, China banned travel to and from Wuhan city on 23 January 2020 andimplemented a national emergency response. We investigated the spread and control of COVID-19using a data set that included case reports, human movement, and public health interventions.The Wuhan shutdown was associated with the delayed arrival of COVID-19 in other cities by2.91 days. Cities that implemented control measures preemptively reported fewer cases on average(13.0) in the first week of their outbreaks compared with cities that started control later (20.6).Suspending intracity public transport, closing entertainment venues, and banning public gatheringswere associated with reductions in case incidence. The national emergency response appears tohave delayed the growth and limited the size of the COVID-19 epidemic in China, averting hundredsof thousands of cases by 19 February (day 50).

On 31 December 2019—less than amonthbefore the 2020 Spring Festival holiday,including the Chinese Lunar New Year—a cluster of pneumonia cases caused byan unknown pathogen was reported in

Wuhan, a city of 11 million inhabitants and thelargest transport hub in Central China. A novelcoronavirus (1, 2) was identified as the etiolog-ical agent (3, 4), and human-to-human trans-mission of the virus [severe acute respiratorysyndrome–coronavirus 2 (SARS-CoV-2)] hasbeen since confirmed (5, 6). Further spatial

spread of this disease was of great concern inview of the upcoming Spring Festival (chunyun),during which there are typically 3 billion travelmovements over the 40-day holiday period,which runs from 15 days before the SpringFestival (Chinese Lunar New Year) to 25 daysafterward (7, 8).Because there is currently neither a vaccine

nor a specific drug treatment for coronavirusdisease 2019 (COVID-19), a range of publichealth (nonpharmaceutical) interventions hasbeen used to control the epidemic. In an at-tempt to prevent further dispersal of COVID-19 from its source, all transport was prohibitedin and out of Wuhan city from 10:00 a.m. on23 January 2020, followed by the whole ofHubei Province a day later. In terms of thepopulation covered, this appears to be thelargest attempted cordon sanitaire in humanhistory.On 23 January, China also raised its national

public health response to the highest state ofemergency: Level 1 of 4 levels of severity in

the Chinese Emergency System, defined as an“extremely serious incident” (9). As part of thenational emergency response, and in additionto the Wuhan city travel ban, suspected andconfirmed cases have been isolated, publictransport by bus and subway rail suspended,schools and entertainment venues have beenclosed, public gatherings banned, health checkscarried out on migrants (“floating population”),travel prohibited in and out of cities, and in-formation widely disseminated. Despite all ofthese measures, COVID-19 remains a dangerin China. Control measures taken in Chinapotentially hold lessons for other countriesaround the world.Although the spatial spread of infectious

diseases has been intensively studied (10–15),including explicit studies of the role of humanmovement (16, 17), the effectiveness of travelrestrictions and social distancing measures inpreventing the spread of infection is uncertain.For COVID-19, SARS-CoV-2 transmission pat-terns and the impact of interventions are stillpoorly understood (6, 7).We therefore carriedout a quantitative analysis to investigate therole of travel restrictions and transmission con-trol measures during the first 50 days of theCOVID-19 epidemic in China, from31December2019 to 19 February 2020 (Fig. 1). This periodencompassed the 40 days of the Spring Festivalholiday, 15 days before the Chinese Lunar NewYear on 25 January and 25 days afterward. Theanalysis is based on a geocoded repository ofdata on COVID-19 epidemiology, human move-ment, and public health (nonpharmaceutical)interventions. These data include the numbersof COVID-19 cases reported eachday in each cityof China, information on 4.3 million humanmovements fromWuhan city, and data on thetiming and type of transmission control mea-sures implemented across cities of China.We first investigated the role of the Wuhan

city travel ban, comparing travel in 2020 withthat in previous years and exploring how holi-day travel links to the dispersal of infectionacross China. During Spring Festival travel in2017 and 2018, there was an average outflowof 5.2 million people fromWuhan city duringthe 15 days before the Chinese LunarNewYear.

RESEARCH

Tian et al., Science 368, 638–642 (2020) 8 May 2020 1 of 5

1State Key Laboratory of Remote Sensing Science, College ofGlobal Change and Earth System Science, Beijing NormalUniversity, Beijing, China. 2School of Mathematical Sciences,University of Southampton, Southampton, UK. 3Departmentof Land, Air and Water Resources, University of CaliforniaDavis, Davis, CA, USA. 4Department of Zoology, University ofOxford, Oxford, UK. 5Harvard Medical School, HarvardUniversity, Boston, MA, USA. 6Boston Children’s Hospital,Boston, MA, USA. 7Ministry of Education Key Laboratory forEarth System Modeling, Department of Earth SystemScience, Tsinghua University, Beijing, China. 8BeijingCenter for Disease Prevention and Control, Beijing, China.9State Key Laboratory of Pathogen and Biosecurity, BeijingInstitute of Microbiology and Epidemiology, Beijing, China.10Department of Urban Planning and Design, The Universityof Hong Kong, Hong Kong. 11Department of Occupational andEnvironmental Health Sciences, School of Public Health,Peking University, China. 12Center for Infectious DiseaseDynamics, Department of Biology, Pennsylvania StateUniversity, University Park, PA, USA. 13Department ofEntomology, College of Agricultural Sciences, PennsylvaniaState University, University Park, PA, USA. 14Division ofInternational Epidemiology and Population Studies, FogartyInternational Center, National Institutes of Health, Bethesda,MD, USA. 15Department of Ecology and Evolutionary Biology,Princeton University, Princeton, NJ, USA. 16Oxford MartinSchool, University of Oxford, Oxford, UK.*These authors contributed equally to this work.†Corresponding author. Email: [email protected] (H.T.);[email protected] (C.D.); [email protected] (O.G.P.);[email protected] (B.T.G.); [email protected] (R.Y.)

Table 1. Association between the Wuhan travel ban and COVID-19 dispersal to other cities inChina. The dependent variable Y is the arrival time (days) of the outbreak in each city.

Covariates Coefficient 95% CI P

Intercept 25.95 (23.43, 28.48) <0.01. ... .. ... ... .. ... ... .. ... .. ... ... .. ... ... .. ... ... .. ... .. ... ... .. ... ... .. ... .. ... ... .. ... ... .. ... ... .. ... .. ... ... .. ... ... .. ... .. ... ... .. ... ... .. ... ... .. ... .. ... ... .. ... ... .. ... .. ... ... .. ... ... .. ... ... .. ... .. ... ... .

Longitude (degrees) –0.03 (–0.05, –0.01) <0.01. ... .. ... ... .. ... ... .. ... .. ... ... .. ... ... .. ... ... .. ... .. ... ... .. ... ... .. ... .. ... ... .. ... ... .. ... ... .. ... .. ... ... .. ... ... .. ... .. ... ... .. ... ... .. ... ... .. ... .. ... ... .. ... ... .. ... .. ... ... .. ... ... .. ... ... .. ... .. ... ... .

Latitude (degrees) 0.03 (0.01, 0.06) <0.05. ... .. ... ... .. ... ... .. ... .. ... ... .. ... ... .. ... ... .. ... .. ... ... .. ... ... .. ... .. ... ... .. ... ... .. ... ... .. ... .. ... ... .. ... ... .. ... .. ... ... .. ... ... .. ... ... .. ... .. ... ... .. ... ... .. ... .. ... ... .. ... ... .. ... ... .. ... .. ... ... .

log10 (population) –0.70 (–1.12, –0.28) <0.01. ... .. ... ... .. ... ... .. ... .. ... ... .. ... ... .. ... ... .. ... .. ... ... .. ... ... .. ... .. ... ... .. ... ... .. ... ... .. ... .. ... ... .. ... ... .. ... .. ... ... .. ... ... .. ... ... .. ... .. ... ... .. ... ... .. ... .. ... ... .. ... ... .. ... ... .. ... .. ... ... .

log10 (total movements) –0.12 (–0.22, –0.02) <0.05. ... .. ... ... .. ... ... .. ... .. ... ... .. ... ... .. ... ... .. ... .. ... ... .. ... ... .. ... .. ... ... .. ... ... .. ... ... .. ... .. ... ... .. ... ... .. ... .. ... ... .. ... ... .. ... ... .. ... .. ... ... .. ... ... .. ... .. ... ... .. ... ... .. ... ... .. ... .. ... ... .

Travel ban (days) 2.91 (2.54, 3.29) <0.01. ... .. ... ... .. ... ... .. ... .. ... ... .. ... ... .. ... ... .. ... .. ... ... .. ... ... .. ... .. ... ... .. ... ... .. ... ... .. ... .. ... ... .. ... ... .. ... .. ... ... .. ... ... .. ... ... .. ... .. ... ... .. ... ... .. ... .. ... ... .. ... ... .. ... ... .. ... .. ... ... .

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In 2020, this travel was interrupted by theWuhan city shutdown, but 4.3 million peopletraveled out of the city between 11 January andthe implementation of the ban on 23 January(Fig. 2A) (7). In 2017 and 2018, travel out of thecity during the 25 days after the Chinese LunarNew Year averaged 6.7 million people eachyear. In 2020, the travel ban prevented almostall of that movement and markedly reducedthe number of exportations of COVID-19 fromWuhan (7, 8).The dispersal of COVID-19 from Wuhan

was rapid (Fig. 3A). A total of 262 citiesreported cases within 28 days. For compari-son, the 2009 influenza H1N1 pandemic took132 days to reach the same number of cities inChina (Supplementary materials, materialsand methods). The number of cities provid-ing first reports of COVID-19 peaked at 59 perday on 23 January, the date of the Wuhantravel ban.The total number of cases reported from

each province by 30 January, 1 week after theWuhan shutdown,was strongly associatedwiththe total number of travellers from Wuhan[correlation coefficient (r) = 0.98, P < 0.01;excluding Hubei, r = 0.69, P < 0.01] (Fig. 2, Band C). COVID-19 arrived sooner in those citiesthat had larger populations and had moretravellers fromWuhan (Table 1 and table S1).However, the Wuhan travel ban was associ-ated with a delayed arrival time of COVID-19in other cities by an estimated 2.91 days [95%confidence interval (CI), 2.54 to 3.29 days] onaverage (Fig. 3B and Table 1).This delay provided extra time to prepare

for the arrival of COVID-19 in more than 130cities across China but would not have curbedtransmission after infection had been exportedto new locations from Wuhan. The timing andimplementationof emergency controlmeasuresin 342 cities across China are shown in Fig. 1(figs. S2 and S4). School closure, the isolationof suspected and confirmed patients, plus thedisclosure of information were implementedin all cities. Public gatheringswere banned andentertainment venues closed in 220 cities(64.3%). Intracity public transport was sus-pended in 136 cities (39.7%), and intercitytravel was prohibited by 219 cities (64.0%).All three measures were applied in 136 cities(table S2).Cities that implemented a Level 1 response

(any combination of control measures) (figs.S2 and S4) preemptively, before discoveringany COVID-19 cases, reported 33.3% (95% CI,11.1 to 44.4%) fewer laboratory-confirmedcases during the first week of their outbreaks(13.0 cases; 95% CI, 7.1 to 18.8, n = 125 cities)compared with cities that started control later(20.6 cases, 95% CI, 14.5 to 26.8, n = 171 cities),with a statistically significant difference be-tween the two groups (Mann-Whitney U =8197, z = –3.4, P < 0.01). A separate analysis

using regression models shows that amongspecific control measures, cities that suspendedintracity public transport and/or closed enter-tainment venues and banned public gather-ings, and did so sooner, had fewer cases duringthe first week of their outbreaks (Table 2 andtable S3). This analysis provided no evidencethat the prohibition of travel between cities,which was implemented after and in additionto the Wuhan shutdown on 23 January, re-duced the number of cases in other cities acrossChina. These results are robust to the choice ofstatistical regression model (table S3).The reported daily incidence of confirmed

cases peaked in Hubei province (includingWuhan) on 4 February (3156 laboratory-confirmed cases, 5.33 per 100,000 popula-tion in Hubei) and in all other provinces on31 January (875 cases, 0.07 per 100,000 pop-ulation) (fig. S1). The low level of peak inci-dence per capita, the early timing of the peak,and the subsequent decline in daily case

reports suggest that transmission controlmeasures were associated not only with adelay in the growth of the epidemic but alsowith a marked reduction in the number ofcases. By fitting an epidemic model to thetime series of cases reported in each province(fig. S3), we estimate that the (basic) case re-production number (R0) was 3.15 before theimplementation of the emergency response on23 January (Table 3). As control was scaled-upfrom 23 January onward (stage 1), the casereproduction number declined to 0.97, 2.01,and 3.05 (estimated as C1R0) in three groupsof provinces, depending on the rate of imple-mentation in each group (Table 3 and tableS4). Once the implementation of interventionswas 95% complete everywhere (stage 2), thecase reproduction number had fallen to 0.04on average (C2R0), far below the replacementrate (≪1) and consistent with the rapid de-cline in incidence (Fig. 4A, Table 3, fig. S5, andtable S4).

Tian et al., Science 368, 638–642 (2020) 8 May 2020 2 of 5

31 Dec. Respiratory disease due to novel coronavirus detected in Wuhan city

23 Jan. Wuhan city travel ban; first 3 provinces begin Level 1 response24 Jan. 14 provinces begin Level 1 response

25 Jan. 13 provinces begin Level 1 response

29 Jan. Last province begins Level 1 response

26 Jan. China State Council approves an extension of the Spring Festival holiday to 2 Feb27 Jan . Ministry of Education postpones start of the spring semester in 2020

20 Jan. Novel coronavirus disease categorized as a Category B infectious disease and managed under Category A infectious diseases

28 Jan. Ministry of Transport refunds all public rail, road, and water travel tickets

30 Jan

21 Jan. Ministry of Transport launches Level 2 emergency

10 Feb. Residential districts in Hubei province put under closedmanagement

3 Feb. Travel permits to Hong Kong and Macau suspended

31 ... 20 21 23 24 25 26 27 28 29 30 3 10

. 14,000 health checkpoints set up at bus and boat terminals,service centers, and toll gates nationwide

Fig. 1. Dates of discovery of the novel coronavirus causing COVID-19 and of the implementation ofcontrol measures in China, from 31 December 2019.

Table 2. Associations between the type and timing of transmission control measures and thenumber of COVID-19 cases reported in city outbreaks the first week. Data were evaluated bymeans of a generalized linear regression model.

Covariates Coefficient 95% CI P

(Intercept) –9.10 (–9.56, –8.64) <0.01. ... .. ... ... .. ... ... .. ... .. ... ... .. ... ... .. ... ... .. ... .. ... ... .. ... ... .. ... .. ... ... .. ... ... .. ... ... .. ... .. ... ... .. ... ... .. ... .. ... ... .. ... ... .. ... ... .. ... .. ... ... .. ... ... .. ... .. ... ... .. ... ... .. ... ... .. ... .. ... ... .

Arrival time 0.44 (0.43, 0.46) <0.01. ... .. ... ... .. ... ... .. ... .. ... ... .. ... ... .. ... ... .. ... .. ... ... .. ... ... .. ... .. ... ... .. ... ... .. ... ... .. ... .. ... ... .. ... ... .. ... .. ... ... .. ... ... .. ... ... .. ... .. ... ... .. ... ... .. ... .. ... ... .. ... ... .. ... ... .. ... .. ... ... .

Distance from Wuhan City (log10) 0.61 (0.49, 0.73) <0.01. ... .. ... ... .. ... ... .. ... .. ... ... .. ... ... .. ... ... .. ... .. ... ... .. ... ... .. ... .. ... ... .. ... ... .. ... ... .. ... .. ... ... .. ... ... .. ... .. ... ... .. ... ... .. ... ... .. ... .. ... ... .. ... ... .. ... .. ... ... .. ... ... .. ... ... .. ... .. ... ... .

Suspension of intra-city public transport. ... .. ... ... .. ... ... .. ... .. ... ... .. ... ... .. ... ... .. ... .. ... ... .. ... ... .. ... .. ... ... .. ... ... .. ... ... .. ... .. ... ... .. ... ... .. ... .. ... ... .. ... ... .. ... ... .. ... .. ... ... .. ... ... .. ... .. ... ... .. ... ... .. ... ... .. ... .. ... ... .

Implementation –3.50 (–4.28, –2.73) <0.01. ... .. ... ... .. ... ... .. ... .. ... ... .. ... ... .. ... ... .. ... .. ... ... .. ... ... .. ... .. ... ... .. ... ... .. ... ... .. ... .. ... ... .. ... ... .. ... .. ... ... .. ... ... .. ... ... .. ... .. ... ... .. ... ... .. ... .. ... ... .. ... ... .. ... ... .. ... .. ... ... .

Timing 0.11 (0.08, 0.14) <0.01. ... .. ... ... .. ... ... .. ... .. ... ... .. ... ... .. ... ... .. ... .. ... ... .. ... ... .. ... .. ... ... .. ... ... .. ... ... .. ... .. ... ... .. ... ... .. ... .. ... ... .. ... ... .. ... ... .. ... .. ... ... .. ... ... .. ... .. ... ... .. ... ... .. ... ... .. ... .. ... ... .

Closure of entertainment venues. ... .. ... ... .. ... ... .. ... .. ... ... .. ... ... .. ... ... .. ... .. ... ... .. ... ... .. ... .. ... ... .. ... ... .. ... ... .. ... .. ... ... .. ... ... .. ... .. ... ... .. ... ... .. ... ... .. ... .. ... ... .. ... ... .. ... .. ... ... .. ... ... .. ... ... .. ... .. ... ... .

Implementation –2.28 (–2.98, –1.57) <0.01. ... .. ... ... .. ... ... .. ... .. ... ... .. ... ... .. ... ... .. ... .. ... ... .. ... ... .. ... .. ... ... .. ... ... .. ... ... .. ... .. ... ... .. ... ... .. ... .. ... ... .. ... ... .. ... ... .. ... .. ... ... .. ... ... .. ... .. ... ... .. ... ... .. ... ... .. ... .. ... ... .

Timing 0.09 (0.06, 0.11) <0.01. ... .. ... ... .. ... ... .. ... .. ... ... .. ... ... .. ... ... .. ... .. ... ... .. ... ... .. ... .. ... ... .. ... ... .. ... ... .. ... .. ... ... .. ... ... .. ... .. ... ... .. ... ... .. ... ... .. ... .. ... ... .. ... ... .. ... .. ... ... .. ... ... .. ... ... .. ... .. ... ... .

RESEARCH | REPORT

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On the basis of the fit of the model to dailycase reports from each province, and on thepreceding statistical analyses, we investigatedthe possible effects of control measures on thetrajectory of the epidemic outside Wuhan city(Fig. 4B). Our model suggests that without theWuhan travel ban or the national emergencyresponse, there would have been 744,000(±156,000) confirmed COVID-19 cases outsideWuhan by 19 February, day 50 of the epidemic.With theWuhan travel ban alone, this numberwould have decreased to 202,000 (±10,000)cases.With the national emergency responsealone (without the Wuhan travel ban), thenumber of cases would have decreased to199,000 (±8500). Thus, neither of these in-terventionswould, on their own, have reversedthe rise in incidence by 19 February (Fig. 4B).But together and interactively, these controlmeasures offer an explanation of why the risein incidence was halted and reversed, limitingthe number of confirmed cases reported to29,839 (fitted model estimate 28,000 ± 1400cases), 96% fewer than expected in the absenceof interventions.This analysis shows that transmission con-

trol (nonpharmaceutical) measures initiatedduring the Chinese Spring Festival holiday,including the unprecedentedWuhan city travelban and the Level 1 national emergency re-sponse, were strongly associatedwith, althoughnot necessarily the cause of, a delay in epidemicgrowth and a reduction in casenumbers duringthe first 50 days of the COVID-19 epidemic inChina.The number of people who have developed

COVID-19 during this epidemic, and thereforethe number of people who were protected bycontrol measures, is not known precisely, giventhat caseswere almost certainly underreported.However, in view of the small fraction of peopleknown to have been infected by 19 February(75,532 cases, 5.41 per 100,000 population), itis unlikely that the spread of infection washalted and epidemic growth reversed becausethe supply of susceptible people had been ex-hausted. This implies that a large fraction of theChinese population remains at risk of COVID-19; controlmeasuresmay need to be reinstated,in some form, if there is a resurgence of trans-mission. Further investigations are needed toverify that proposition, and population sur-veys of infection are needed to reveal the truenumber of people who have been exposed tothis novel coronavirus.We could not investigate the impact of all

elements of the national emergency responsebecause many were introduced simultaneouslyacross China. However, this analysis shows thatsuspending intracity public transport, closingentertainment venues, and banning publicgatherings, which were introduced at differ-ent times in different places, were associatedwith the overall containment of the epidemic.

Tian et al., Science 368, 638–642 (2020) 8 May 2020 3 of 5

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Travel movements from Wuhan to each province before Spring Festival in 2020

Fig. 2. The dispersal of COVID-19 in China 15 days before and 25 days after the Spring Festival(Chinese Lunar New Year). (A) Movement outflows from Wuhan city during Spring Festival travel in2017, 2018, and 2020. The vertical dotted line is the date of the Spring Festival (Chinese Lunar NewYear). (B) The number of recorded movements from Wuhan city to other provinces during the 15 daysbefore the Spring Festival in 2020. The shading from light to dark represents the number of humanmovements from Wuhan to each province. The areas of circles represent the cumulative number ofcases reported by 30 January 2020, 1 week after the Wuhan travel ban on 23 January. (C) Associationbetween the cumulative number of confirmed cases reported before 30 January and the number ofmovements from Wuhan to other provinces.

Table 3. Parameter estimates of the SEIR (susceptible-exposed-infectious-recovered) epi-demic model. BCI, Bayesian confidence interval; C1_high, Heilongjiang, Shanghai, Tianjin, Zhejiang, andHubei (excluding Wuhan); C1_medium, Anhui, Beijing, Fujian, Guangdong, Guangxi, Guizhou, Hunan, Jilin,Jiangsu, Jiangxi, Inner Mongolia, Shandong, and Tibet; C1_low, Gansu, Hainan, Hebei, Henan, Liaoning,Ningxia, Qinghai, Shanxi, Shaanxi, Sichuan, Xinjiang, Yunnan, and Chongqing.

Parameter Definition Mean 95% BCI

r Reporting proportion 0.002 0.001 to 0.003.. .. ... ... .. ... .. ... ... .. ... ... .. ... .. ... ... .. ... ... .. ... ... .. ... .. ... ... .. ... ... .. ... .. ... ... .. ... ... .. ... ... .. ... .. ... ... .. ... ... .. ... .. ... ... .. ... ... .. ... ... .. ... .. ... ... .. ... ... .. ... .. ... ... .. ... ... .. ... ... .. .

R0 Basic reproduction number 3.15 3.04 to 3.26.. .. ... ... .. ... .. ... ... .. ... ... .. ... .. ... ... .. ... ... .. ... ... .. ... .. ... ... .. ... ... .. ... .. ... ... .. ... ... .. ... ... .. ... .. ... ... .. ... ... .. ... .. ... ... .. ... ... .. ... ... .. ... .. ... ... .. ... ... .. ... .. ... ... .. ... ... .. ... ... .. .

1/d Mean latent period (days) 4.90 4.32 to 5.47.. .. ... ... .. ... .. ... ... .. ... ... .. ... .. ... ... .. ... ... .. ... ... .. ... .. ... ... .. ... ... .. ... .. ... ... .. ... ... .. ... ... .. ... .. ... ... .. ... ... .. ... .. ... ... .. ... ... .. ... ... .. ... .. ... ... .. ... ... .. ... .. ... ... .. ... ... .. ... ... .. .

C1_high Lower effect of control at the first stage 0.97 0.94 to 0.99.. .. ... ... .. ... .. ... ... .. ... ... .. ... .. ... ... .. ... ... .. ... ... .. ... .. ... ... .. ... ... .. ... .. ... ... .. ... ... .. ... ... .. ... .. ... ... .. ... ... .. ... .. ... ... .. ... ... .. ... ... .. ... .. ... ... .. ... ... .. ... .. ... ... .. ... ... .. ... ... .. .

C1_medium Medium effect of control at the first stage 0.65 0.58 to 0.72.. .. ... ... .. ... .. ... ... .. ... ... .. ... .. ... ... .. ... ... .. ... ... .. ... .. ... ... .. ... ... .. ... .. ... ... .. ... ... .. ... ... .. ... .. ... ... .. ... ... .. ... .. ... ... .. ... ... .. ... ... .. ... .. ... ... .. ... ... .. ... .. ... ... .. ... ... .. ... ... .. .

C1_low Higher effect of control at the first stage 0.31 0.24 to 0.38.. .. ... ... .. ... .. ... ... .. ... ... .. ... .. ... ... .. ... ... .. ... ... .. ... .. ... ... .. ... ... .. ... .. ... ... .. ... ... .. ... ... .. ... .. ... ... .. ... ... .. ... .. ... ... .. ... ... .. ... ... .. ... .. ... ... .. ... ... .. ... .. ... ... .. ... ... .. ... ... .. .

C2 Effect of control at the second stage 0.01 0.001 to 0.03.. .. ... ... .. ... .. ... ... .. ... ... .. ... .. ... ... .. ... ... .. ... ... .. ... .. ... ... .. ... ... .. ... .. ... ... .. ... ... .. ... ... .. ... .. ... ... .. ... ... .. ... .. ... ... .. ... ... .. ... ... .. ... .. ... ... .. ... ... .. ... .. ... ... .. ... ... .. ... ... .. .

1/g Infectious period before isolation (days) 5.19 4.51 to 5.86.. .. ... ... .. ... .. ... ... .. ... ... .. ... .. ... ... .. ... ... .. ... ... .. ... .. ... ... .. ... ... .. ... .. ... ... .. ... ... .. ... ... .. ... .. ... ... .. ... ... .. ... .. ... ... .. ... ... .. ... ... .. ... .. ... ... .. ... ... .. ... .. ... ... .. ... ... .. ... ... .. .

Iw0 Minimum number of cases when none detected 1.12 0.91 to 1.32.. .. ... ... .. ... .. ... ... .. ... ... .. ... .. ... ... .. ... ... .. ... ... .. ... .. ... ... .. ... ... .. ... .. ... ... .. ... ... .. ... ... .. ... .. ... ... .. ... ... .. ... .. ... ... .. ... ... .. ... ... .. ... .. ... ... .. ... ... .. ... .. ... ... .. ... ... .. ... ... .. .

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However, other factors are likely to have con-tributed to control, especially the isolation ofsuspected and confirmed patients and theircontact, and it is not yet clear which parts ofthe national emergency response were mosteffective. We did not find evidence that pro-hibiting travel between cities or provinces re-duced the numbers of COVID-19 cases outsideWuhan and Hubei, perhaps because suchtravel bans were implemented as a responseto, rather than in anticipation of, the arrivalof COVID-19.This study has drawn inferences not from

controlled experiments but from statisticaland mathematical analyses of the temporaland spatial variation in case reports, humanmobility, and transmission control measures.With that caveat, control measures were stronglyassociated with the containment of COVID-19,potentially averting hundreds of thousands ofcases by 19 February, day 50 of the epidemic.Whether the means and the outcomes of con-

trol can be replicated outside China and whichof the interventions are most effective are nowunder intense investigation as the virus con-tinues to spread worldwide.

REFERENCES AND NOTES

1. N. Zhu et al., N. Engl. J. Med. 382, 727–733 (2020).2. R. Lu et al., Lancet 395, 565–574 (2020).3. F. Wu et al., Nature 579, 265–269 (2020).4. P. Zhou et al., Nature 579, 270–273 (2020).5. J. Cai et al., Int. J. Environ. Res. Public Health 16, 222

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ACKNOWLEDGMENTS

We thank the thousands of Centers for Disease Control (CDC)staff and local health workers in China who collected data andcontinue to work to contain COVID-19 in China and elsewhere.Funding: This study was provided by the National Natural ScienceFoundation of China (81673234), Beijing Natural ScienceFoundation (JQ18025), Beijing Advanced Innovation Program forLand Surface Science, and Young Elite Scientist SponsorshipProgram by CAST (YESS) (2018QNRC001). H.T., M.U.G.K., O.G.P.,and C.D. acknowledge support from the Oxford Martin School;H.T. acknowledges support from the Military Logistics ResearchProgram. The funders had no role in study design, data collectionand analysis, the decision to publish, or in preparation of themanuscript. Author contributions: H.T., P.Z., R.Y., O.G.P.,B.T.G., and C.D. designed the study. B.C. and Y.S. collected andprocessed the Tencent’s LBS data. Y.Liu, B.L., B.X., Q.Y.,B.W., P.Y., Y.C., and Q.W. collected the statistical data. H.T.,Y.Li, C.-H.W., and J.C. conducted the analyses. M.U.G.K., O.N.B.,

Tian et al., Science 368, 638–642 (2020) 8 May 2020 4 of 5

Fig. 3. Spatial dispersal of COVID-19 inChina. (A) Cumulative number of citiesreporting cases by 19 February 2020.Arrival days are defined as the timeinterval (days) from the date of the firstcase in the first infected city (Wuhan) tothe date of the first case in each newlyinfected city (a total of 324 cities), tocharacterize the intercity transmission rateof COVID-19. The dashed line indicates thedate of the Wuhan travel ban (shutdown).(B) Before (blue) and after (red) theintervention by 30 January 2020, 1 weekafter the Wuhan travel ban (shutdown). Theblue line and points show the fittedregression of arrival times up to theshutdown on day 23 (23 January, verticaldashed line). Gray points show the expected arrival times after day 23, without the shutdown. The red line and points show the fitted regression of delayed arrivaltimes after the shutdown on day 23. Each observation (point) represents one city. Error bars give ±2 standard deviations.

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Fig. 4. The role of interventions incontrolling the COVID-19 outbreakacross China. (A) Epidemic model(line) fitted to daily reports of confirmedcases (points) summed across 31provinces. Hubei excludes Wuhan city.(B) Expected epidemic trajectories with-out the Wuhan travel ban (shutdown),and with (blue) or without (red) inter-ventions carried out as part of the Level 1national emergency response, with theWuhan travel ban and with (black) orwithout (orange) the intervention. Verticaldashed lines in (A) and (B) mark thedate of the Wuhan travel ban and thestart of the emergency response on23 January. Shaded regions in (A) and (B)mark the 95% prediction envelopes.

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R.Y., O.G.P., B.T.G., and C.D. edited the manuscript. H.T. andC.D. wrote the manuscript. All authors read and approved themanuscript. Competing interests: All other authors declare nocompeting interests. Data and materials availability: Codeand data are available on the following GitHub repository:https://github.com/huaiyutian/COVID-19_TCM-50d_China (18).This work is licensed under a Creative Commons Attribution 4.0International (CC BY 4.0) license, which permits unrestricteduse, distribution, and reproduction in any medium, provided the

original work is properly cited. To view a copy of this license, visithttps://creativecommons.org/licenses/by/4.0/. This license doesnot apply to figures/photos/artwork or other content included inthe article that is credited to a third party; obtain authorization fromthe rights holder before using such material.

SUPPLEMENTARY MATERIALS

science.sciencemag.org/content/368/6491/638/suppl/DC1Materials and Methods

Figs. S1 to S7Tables S1 to S4References (19–28)

View/request a protocol for this paper from Bio-protocol.

6 March 2020; accepted 27 March 2020Published online 31 March 202010.1126/science.abb6105

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epidemic in ChinaAn investigation of transmission control measures during the first 50 days of the COVID-19

Oliver G. Pybus and Christopher DyeBen Wang, Peng Yang, Yujun Cui, Yimeng Song, Pai Zheng, Quanyi Wang, Ottar N. Bjornstad, Ruifu Yang, Bryan T. Grenfell, Huaiyu Tian, Yonghong Liu, Yidan Li, Chieh-Hsi Wu, Bin Chen, Moritz U. G. Kraemer, Bingying Li, Jun Cai, Bo Xu, Qiqi Yang,

originally published online March 31, 2020DOI: 10.1126/science.abb6105 (6491), 638-642.368Science 

, this issue p. 638Sciencecontrol measures could lead to a resurgence.infection. It is unlikely that this decline happened because the supply of susceptible people was exhausted, so relaxingtransport and entertainment venues and banning public gatherings combined to avert hundreds of thousands of cases of the epidemic peaked in Hubei province on 4 February 2020, indicating that measures such as closing citywide publicrestrictions in and out of Wuhan were too late to prevent the spread of the virus to 262 cities within 28 days. However, encompasses the Lunar New Year period when millions of people traveled across China for family visits. Travelquantitative analysis of the impact of control measures between 31 December 2019 and 19 February 2020, which

performed aet al.coronavirus 2 (SARS-CoV-2). However, which measures were most effective is uncertain. Tian −distancing measures on its populace in an attempt to inhibit the transmission of severe acute respiratory syndrome By 23 January 2020, China had imposed a national emergency response to restrict travel and impose social

The most effective interventions

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